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A nomogram for predicting residual low back pain after percutaneous kyphoplasty in osteoporotic vertebral compression fractures

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Abstract

Summary

To establish a risk prediction model for residual low back pain after percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures. We used retrospective data for model construction and evaluated the model using internal validation and temporal external validation and finally concluded that the model had good predictive performance.

Introduction

The cause of residual low back pain in patients with osteoporotic vertebral compression fractures (OVCFs) after PKP remains highly controversial, and our goal was to investigate the most likely cause and to develop a novel nomogram for the prediction of residual low back pain and to evaluate the predictive performance of the model.

Methods

The clinical data of 281 patients with OVCFs who underwent PKP at our hospital from July 2019 to July 2020 were reviewed. The optimal logistic regression model was determined by lasso regression for multivariate analysis, thus constructing a nomogram. Bootstrap was used to perfomance the internal validation; receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were used to assess the predictive performance and clinical utility of the model, respectively. Temporal external validation of the model was also performed using retrospective data from 126 patients who underwent PKP at our hospital from January 2021 to October 2021.

Results

Lasso regression cross-validation showed that the variables with non-zero coefficients were the number of surgical vertebrae, preoperative bone mineral density (pre-BMD), smoking history, thoracolumbar fascia injury (TLFI), intraoperative facet joint injury (FJI), and postoperative incomplete cementing of the fracture line (ICFL). The above factors were included in the multivariate analysis and showed that the pre-BMD, smoking history, TLFI, FJI, and ICFL were independent risk factors for residual low back pain (P < 0.05). The ROC and calibration curve of the original model and temporal external validation indicated a good predictive power of the model. The DCA curve suggested that the model has good clinical practicability.

Conclusion

The risk prediction model has good predictive performance and clinical practicability, which can provide a certain basis for clinical decision-making in patients with OVCFs.

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Data availability

All data generated or used during the study are available from the corresponding author and first author upon reasonable request.

Abbreviations

OVCFs:

osteoporotic vertebral compression fractures

PVP:

percutaneous vertebroplasty

PKP:

percutaneous kyphoplasty

FJI:

facet joint injury

CIV:

bone cement injection volume

TLFI:

thoracolumbar fascia injury

BMD:

bone mineral density

VAS:

visual analogue score

ODI:

Oswestry Disability Index

VBCR:

vertebral body compression rate

LKA:

local kyphotic Cobb’s angle

Lasso:

least absolute shrinkage and selection operator

ROC:

receiver operating characteristic

DCA:

decision curve analysis

ICFL:

incomplete cementing of the fracture line

C-statistics:

concordance statistics

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Acknowledgements

We would like to acknowledge Guy Romeo Kenmegne (West China School of Medicine, Sichuan University) for editing this manuscript.

Funding

This study was funded by Dalian Science and Technology Innovation Fund (grant number: 2021JJ13SN68).

Author information

Authors and Affiliations

  1. Department of Orthopaedics, Affiliated Zhongshan Hospital of Dalian University, No.6, Jiefang Street, Dalian, Liaoning Province, 116001, China

    Miaoman Lin, Hao Zhang, Xingxing Huang, Cunheng Yang, Fuming Wang, Junxiao Gao, Meng Zhang & Xiaobing Yu

  2. Department of Orthopaedics, West China Xiamen Hospital of Sichuan University, No.699, West Jinyuan Road, Xingbin Street, Xiamen, Fujian Province, 361022, China

    Miaoman Lin

  3. Xinhua Clinical College, Dalian University, Dalian, 116622, China

    Xuemei Wen

  4. Guangzhou University of Chinese Medicine, Guangzhou, 510006, China

    Zongwei Huang

  5. Department of Emergency, Beijing University of Chinese Medicine Shenzhen Hospital, Shenzhen, 518116, China

    Zongwei Huang

  6. Department of Orthopaedics, Dongguan Tungwah Hospital, Dongguan, 523000, China

    Wei Huang

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  1. Miaoman Lin
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Corresponding author

Correspondence to Xiaobing Yu.

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Ethics approval

This study was approved by the Ethics Committee of Affiliated Zhongshan Hospital of Dalian University (Ethics Approval Number:2021085). Because this study was conducted in accordance with the Declaration of Helsinki, and which was a retrospective study and did not involve the privacy of patients, so informed consent was waived from the patients.

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Lin, M., Wen, X., Huang, Z. et al. A nomogram for predicting residual low back pain after percutaneous kyphoplasty in osteoporotic vertebral compression fractures. Osteoporos Int 34, 749–762 (2023). https://doi.org/10.1007/s00198-023-06681-2

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